Abstract

Studies were conducted by Minera Escondida, Ltda. (MEL) between 1995 and 2003 to support an investment decision to open Escondida Norte, an enriched porphyry copper deposit adjacent to the Escondida mine and processing facilities. Due to the importance of copper-iron sulphide minerals in predicting metallurgical performance in both process alternatives, a quantitative spatial model of copper-iron sulphide mineral abundances was determined to be a critical study component.

A suite of total and partial copper analyses already in common use was chosen to maximize relative selectivity among the major copper sulphide minerals in the mineral deposit. These analyses were merged with partial and total sulphur analysis and combined with a novel approach to interpret the analytical results as normative mineral estimates of chalcocite, covellite, chalcopyrite and pyrite content. Development and validation of the normative mineral estimates included verification on the analytical stability and reproducibility of the chemical analyses, determination of extraction rates on synthetic mineral standards, and comparison with modal mineral abundance on natural ore samples. Uncertainty of individual normative copper sulphide minerals is estimated at ±5% (95% confidence interval), while uncertainty on pyrite content is ±12%. The uncertainty of the normative mineral estimates are comparable to uncertainty of corresponding modal mineral estimates, and differences between modal and normative estimates are largely within the estimation uncertainty.

While the methods were originally developed for a simple association based on supergene chalcocite ± covellite replacing and overprinting hypogene chalcopyrite + pyrite, subsequent work developed normative mineral models for bornite + chalcopyrite hypogene and mixed copper oxide-sulphide supergene mineralization.

Escondida Norte, a large supergene-enriched porphyry copper deposit in northern Chile, was discovered in 1981 along with the nearby La Escondida deposit (Lowell 1991; Ortíz 1995). Development drilling and prefeasibility studies were initiated by the Minera Escondida Ltda. joint venture in late 1995 to examine the potential of Escondida Norte to expand mine capacity from the producing Escondida mine. Final feasibility studies were approved by BHP Billiton and its joint venture partners in 2003, and pre-development stripping of the ore body was completed in October 2005.

Prefeasibility and feasibility studies included the evaluation of several process alternatives, all of which included sulphide heap leaching as a low-cost alternative or supplement to traditional milling and flotation. Economic and technical trade-off studies on these options involved forecasts of leaching rates, mill recovery, and concentrate grade, all of which depend on knowing copper-iron sulphide mineralogy of the deposit. In addition, a reliable spatial model of the sulphide mineral content was an important input for determination of final pit limits in the context of sulphide heap leaching economics. It was therefore decided in early 1998 that a quantitative estimate of the spatial distribution of copper and iron sulphide mineralogy was an important component of the project's feasibility study to evaluate the optimal development path.

In this paper, derived from an internal Minera Escondida Ltda. document (Williams et al. 2000) and summarized by Preece et al. (1999), we describe the development path of the method selected to estimate the sulphide mineral content of drill hole composite samples. Analytical protocols for chemical analyses that only partially extract copper and sulphur were adopted by the project. A novel approach to quantitatively estimate the normative sulphide mineral content from results of the analytical suite was developed and tested against modal mineral abundances. As the method has since been expanded into other geological environments, a brief overview of subsequent expansion of this methodology is also provided. The geological, mineralogical and economic context of this study are described in companion paper currently in preparation, along with the implications of the normative mineral estimates.

Previous work

Standard industry practices for the estimation of copper mineral content were largely based on determination of modal mineral content, using methods such as visual logging, optical microscopy, or automated image analysis. Because observations made with these alternative methods provide critical information concerning the distribution and habit of sulphide and gangue minerals, they all played their roles during project evaluation. However, each method comes with drawbacks if implemented on a widespread basis as part of the routine drill core analytical suite. These include high error rates of visual logging estimates and elevated cost and turnaround time for microscopy and automated quantitative mineral analysis, particularly at the time of this study. However, chemical methods showed promise for quantitative assessment of mineral comportment of copper based on their low cost and rapid turnaround and their ability to distinguish among the important copper minerals that comprise the Escondida Norte sulphide ores (Table 1).

Mineral-specific chemical analysis, commonly termed diagnostic leach tests, had been used largely as proxies for industrial-scale copper leaching processes. Brown & Sullivan (1934), for example, conducted a comprehensive study in the use of sulphuric acid plus ferric sulphate lixiviant to extract copper from various oxide and sulphide minerals, reporting moderate solubility of chalcocite, and limited response from covellite and chalcopyrite. The ferric sulphate–soluble copper analysis was subsequently developed by workers in the copper industry as a bench-scale analogue to the sulphide leaching environment. The ratio of soluble copper to total copper in sulphide mineralization is typically viewed as a qualitative to semi-quantitative indicator of chalcocite content (e.g. Bilson 1989; Gurtler 1990). Several studies have shown that most copper sulphides of interest to this study are also highly soluble in sodium cyanide solutions, excluding chalcopyrite (Table 1). These studies generally consisted of metallurgical investigations, carried out to characterize mineral and lixiviant behaviour for copper or gold leach operations.

Multiple selective leach tests, commonly performed in a sequence, have been since developed as a chemical tool to characterize mineralogical variability of mineral deposits. Young (1974) listed several sequential analysis protocols for partially oxidized ores, tailings, and roasted calcine, some dating to the late 1950s. A highly influential study by Parkison & Bhappu (1995), developed a three-step protocol for ore-grade samples that applies a sequence of sulphuric acid, sodium cyanide, and hydrochloric-nitric-perchloric acid digestions to a single sub-sample. More complicated sequential analysis protocols were developed for use in exploration and environmental geochemical studies, seeking to distinguish exotic v. detrital deportment of metals (e.g. Hall et al. 1996; Dold 2003; Kelley et al. 2003). The analytical results of these sequential assays were generally interpreted as semi-quantitative estimates for mineral-based sources of extractable metal.

More recently, development of small scale leach tests were developed by CSIRO within the AMIRA P843a project to determine gold and copper deportment in oxide and sulphide samples. Kuhar et al. (2011) proposed a set of diagnostic chemical analysis performed in parallel to develop a leaching index related to copper mineralogy. Subsequent studies developed methods to improve information on mineral extraction rates from multiple diagnostic leach procedures and the subsequent calculation of normative mineral abundances (Benvie et al. 2013; Kuhar et al. 2013). While each digestion was performed in parallel, the normative equations were formulated and solved in a sequential manner.

Precursor geological studies carried out by project geologists included logging of diamond drill core that mapped the identity and relative abundances of copper minerals throughout the Escondida Norte deposit. Sulphide minerals identified within and below the chalcocite enrichment blanket are predominately chalcocite, covellite, chalcopyrite and pyrite. Detailed petrographic studies had identified accessory sulphides such as bornite, idaite (Cu3FeS4, Sillitoe & Clark 1969), enargite and tennantite to have relatively widespread distributions, but rarely occurring in significant amounts. Construction of a quantitative mineralogical model was therefore focussed on the four dominant minerals.

Methods and results

Ferric sulphate plus sulphuric acid and sodium cyanide analyses combine to uniquely identify the three copper sulphides of interest as each mineral has a distinct pair of responses to the two analyses (Table 1). Importantly, because of their widespread use in copper operations and project development, the analytical techniques were well understood and inexpensive offerings of commercial laboratories. Estimates of pyrite content required the addition of a sulphide sulphur analysis, as preliminary studies showed that iron content included contributions from non-sulphide sources, such as chlorite and biotite. Analyses were performed in parallel, rather than sequential, to eliminate the dependency on the assumption that a partial extraction analyses is specific to a single mineral. In addition, standard quality control protocols can be easily implemented to independently monitor and control the quality of each assay.

To achieve reasonably accurate estimates of normative mineral compositions, a suite of chemical analyses were identified and tested for repeatability against the target minerals. Mineral-specific extraction rates by each of the selected analytic methods were calibrated from a set of synthetic and natural mineral separates of the targeted minerals. Composite samples from the ongoing development drilling program were prepared and submitted for standard petrographic modal mineral analysis to compare and verify normative mineral estimates.

Analytical methods

Chemical analyses for the development stage of the partial extraction program were performed by Actlab-Skyline Laboratories (currently Skyline Assayers and Laboratories) in Tucson, Arizona, USA. Skyline also conducted the bulk of the routine partial extraction analyses through 2002 during implementation of the program into the Escondida Norte project. Beginning in 2001, analytical work for project was gradually transferred to Verilab, SA (currently SGS Chile) in Antofagasta, Chile.

Total copper

Total copper (TCu) was determined by digestion of 0.2 grams of sample in boiling hydrochloric-nitric-perchloric acid taken to dryness. The residue is then dissolved in boiling hydrochloric acid, filtered, and diluted. Copper concentrations were determined spectrographically by atomic absorption. An alternative method was developed for samples of less than 0.5% Cu in which 1 gram of sample was analysed with the same digestion and dilution volume to achieve a lower detection limit (Preece 1999). A detection limit and reporting precision of 0.01% Cu is obtained from the normal (0.2-gram) method of the total and partial copper analyses, while the 1-gram version was reported at precision of 0.001% Cu.

Cyanide soluble copper

Depending on TCu grade, the cyanide soluble copper (CNCu) analysis is based on either 0.2 grams or 1 gram of sample pulp are digested for 30 minutes at room temperature in 10% sodium cyanide on a mechanical shaker. The solution is decanted into a test tube, the residue washed, filtered, and brought to a standard dilution. The copper concentration is determined spectrographically using atomic absorption. As described above, the 0.2-gram charge is part of the standard method with analytical precision of 0.01% CNCu, while a 1-gram method was developed to achieve higher precision (0.001% CNCu) on low-grade samples, and is performed on samples less than 0.5% TCu.

Ferric sulphate soluble copper

The ferric sulphate soluble copper (FSCu) used either 0.25 grams or 1 gram of sample pulp, digested for 60 minutes at room temperature in a solution of 50 g/l sulphuric acid and 5 g/l ferric sulphate. After washing the residue and filtration, the solution is brought to a standard dilution and copper content is determined spectrographically using atomic absorption. Most analyses were performed on the normal (0.25-gram sample), while the 1-gram method is used on samples with less than 0.5% TCu, and reported at 0.01% or 0.001% Cu, respectively.

Iron

Iron (Fe) analyses were determined spectrographically using atomic absorption on the same digestion protocol used for total copper analysis. All iron analyses were reported at a detection limit and precision of 0.01% Fe.

Sulphide sulphur

Sulphur determinations consist of total sulphur (TS), sulphide sulphur (S2) and sulphate sulphur (SO4). Total sulphur was measured on a high frequency infrared Eltra CS 800 spectrometer on weighed samples combusted in an oxygen atmosphere with an induction furnace. The sulphur dioxide gas is filtered for dust and water vapor and measured by solid state infrared analysers. Analyses were reported at a detection limit and precision of 0.01% S.

Sulphide sulphur was determined by washing a 0.5 gram sample with 5% Na2CO3 solution heated briefly to a weak boil, then filtered and dried. Sulphur content of the solid residue was then determined by infrared spectroscopy, and reported at a precision of 0.01% S. Sulphate sulphur was calculated from the difference between total sulphur and sulphide sulphur.

Partial extraction calibration samples

Partial extraction copper analyses were performed on a suite of mineral standards to determine analytical extraction values of the various copper-iron sulphide minerals found in the Escondida Norte deposit. In addition to mineral standards of the dominant copper-iron sulphides chalcocite, covellite, chalcopyrite and pyrite, samples of djurleite, bornite, enargite, tennantite and sulphate minerals were also constructed for this study. The identity, source and sulphide mineralogy of the calibration samples are presented in Table 2.

Synthetic samples of copper mineral separates were constructed from hand-picked minerals from coarsely crushed samples under a binocular microscope, analysed by X-ray diffraction (XRD) analysis to confirm mineral purity, and mixed with unconsolidated gravel collected from the San Manuel Formation near San Manuel, Arizona. The mineral separates and blanks were crushed to nominal −80 mesh, weighed to obtain about 1% Cu, blended and pulverized to −150 mesh for chemical analysis. Three natural samples listed in Table 2 were included in the study, as they contained appropriate purity and abundance levels of the targeted mineral, as determined from optical microscopy, XRD, and chemical analysis.

Normative Mineralogy Verification Samples

A total of thirteen samples were selected from the Escondida Norte development drilling program to verify normative mineral estimates obtained from calibrated partial extraction analyses. The samples were chosen from 15-meter physical composites to obtain as wide a range as possible in copper sulphide mineral composition, at a content of c. 1 wt. % TCu. Samples were riffle split from crushed (nominal −10 mesh) rejects that was sieved with Tyler series screens into four size fractions: −10/+28, −28/+48, −48/+100 and −100 mesh. Duplicate lots were split and prepared from each of the four size fractions, one each for standard partial extraction chemical analysis and reflected light microscopy. Individual samples were labelled according to drill hole name, down-hole meterage of the composite sample, and size fraction.

The suite of partial extraction analysis included TCu, FSCu, CNCu, sulphide sulphur, and iron, with a single set of analyses completed on each of the 52 size fractions. Blind control samples were inserted at a frequency of 1 IRM per 13 unknowns, and monitored to control accuracy. Upon completion of the petrographic studies, the light mineral separates from the four size fractions of one drill hole sample were retrieved and submitted for partial extraction analysis to calculated the mass balance of heavy mineral separation.

Samples were submitted to Dr W. X. Chávez, Jr. of the New Mexico Institute of Mining and Technology, Socorro, New Mexico, USA for the microscopic determination of sulphide mineralogy (Chávez 1999). The size fraction samples were weighed without further comminution into 30 g aliquots and gravity-separated into heavy and light mineral fractions in sodium metatungstate medium. The gravity separates were filtered, washed, dried and weighed, and the heavy mineral fraction was mounted in cold-setting epoxy. Each heavy mineral mount was cut along the vertical axis, re-mounted with other composite size fractions in cold-setting epoxy, ground to a flat surface, and polished. The resulting polished section was an epoxy plug c. 20 mm wide by 30 mm long, each section containing the four size fraction mounts of a single drill hole composite. Standard line counting techniques were used to estimate the relative volume percent of the reflective minerals, with 800 – 1200 counts of opaque minerals per polished section. Conversion to weight percent mineral in the full sample was calculated from the weight fraction of the heavy mineral separates, and adjusted by the ratio of the actual copper assay to copper calculated from modal mineral content.

Sulphide sulphur verification samples

Effectiveness of the sulphide sulphur analysis was studied at the BHP Billiton Newcastle Technology Centre in 2003 for minerals common to sulphide heap leach head and residue material (P. Shrestha, pers. comm.). Composition of mineral separate samples of pyrite, gypsum, and sodium jarosite was confirmed by chemical analysis performed in duplicate with sodium peroxide fusion and ICP-OES finish.

Two synthetic mixtures of the minerals were prepared by blending measured weights of mineral separates with high-purity quartz. The targeted sulphur content in both samples was 6 wt. % sulphur as pyrite and 1.9 wt. % sulphur in sulphate minerals. One sample included jarosite as the only sulphate-bearing mineral, while the second mixed equal parts of jarosite and gypsum to obtain 1.9 wt. % sulphate sulphur.

Sulphate solubility was determined for the mineral separates and synthetic mixtures using a 5% Na2CO3 digestion for 30 minutes at 80°C, followed by ICP-OES of the leach solute. Sulphide sulphur of the synthetic mixtures was determined by LECO infrared spectrometry of the leached residue. All tests were performed in duplicate.

Analytical quality

Quality of copper analyses performed during the Escondida Norte project development study was controlled by monitoring partial extraction values of blind internal reference material (IRM) samples inserted in the sample stream at a frequency of c. 1 in 15 samples. Accuracy of the IRM copper analyses were monitored against tolerance limits of ±10% from the accepted value. In those rare cases of assays that exceeded the tolerance limit, the sequence of samples adjacent to the IRM sample were re-assayed for the non-compliant constituent(s).

The project determined analytical precision through the evaluation of blind replicate and duplicate pulp samples that included c. 7% of the samples. Precision determined during the initial study was based on the methods proposed by Thompson & Howarth (1976), but were since modified according to the recommendations of Stanley & Lawie (2008). All three copper analyses closely followed the same two-factor analytical precision model, which were combined into a single copper model that estimates the effective detection limit at 0.01% Cu and relative precision of ±4.4% (95% confidence interval) at the population average value of 0.8% Cu. The precision model of duplicate sulphide sulphur analyses calculated an effective detection limit of 0.14% S2 and relative precision of ±12% at the average sulphur value of 2.4% S2.

Calibration samples for the current study were submitted with blind IRM samples, as per project control protocols, and each analysis was repeated in triplicate. Analytical results reported for the calibration samples are based on average and standard deviation of the replicate analyses. Verification samples were submitted for partial extraction analysis with IRM samples for accuracy, but without duplicate or replicate samples for analytical precision. Analytical precision of these samples in this study are reported according to the analytical precision model derived from the modified Thompson-Howarth method.

Uncertainty of the modal mineral content determined for the calibration samples was estimated at the 95% confidence interval by the graphical method of van der Plas & Tobi (1965). However, this uncertainty also depends on the efficiency of heavy mineral separation, which was evaluated by partial extraction analysis of the light mineral rejects of the separation process of one sample. Mass balance calculations for the assays found that the method of estimating modal mineral content was affected by the presence of occluded sulphides in the light fraction and entrained non-sulphides in the heavy fraction that were not captured in the point counts. These factors are especially important in the two coarser fractions, which were therefore not used to verify normative mineral estimates in samples with complex mineralogy. The coarse fractions essentially composed of a single copper mineral were used to support calibration of the mineral extraction rates.

Even with improved physical separation in the two fine size fractions (−48/+100 mesh and −100 mesh fractions), separation inefficiency is still an important source of variability in the modal mineral estimate. Mass balance calculations for the head sample and light mineral fraction showed that on average 80% of total sulphides reported to the heavy fraction, the remaining sulphides rejected into the light fraction. While normative copper sulphides were similar in the head sample and light fraction, pyrite was preferentially recovered compared to copper sulphides. The bias in pyrite recovery can be detected in nearly all samples based on systematic differences of copper and sulphur in chemical analyses compared to those calculated from the modal estimates. Thus while modal ratios of copper minerals appear to be reasonably well estimated, this confidence cannot be extended to copper mineral to pyrite ratios.

Results

Total copper, ferric-soluble copper, and cyanide-soluble copper values were determined for the calibration samples by three replicate analyses, which are summarized in Table 3 as averages and standard deviations of the triplicate assays. Precision of low grade copper values was improved by using the 1-gram method for those analyses less than 0.15 wt. % Cu. The average partial extraction ratios presented in Table 3 were calculated as the ratio of the average partial extraction value to the average total copper value for each sample. Standard deviation of the calculated ratio is estimated according to the method of Koch & Link (1980).

Results from partial extraction analysis and modal mineral microscopy of the verification samples are presented in Table 4. Total copper grades of the samples cluster around 1 wt. %, as per design, with an overall range of 0.7 – 2 wt.%. The CNCu and FSCu values, on the other hand, range from near zero to values close to TCu content, reflecting the variations in copper sulphide mineralogy. Smaller differences exist among different size fractions of a single sample, mainly seen in the copper analyses that tend to increase with decreasing particle size.

The mineragraphic study by Chávez (1999) reported on the mineralogy, paragenesis, textures of the opaque mineral assemblage in each size fraction, in addition to the line count data. Qualitative results of the study corroborated the mineral assumptions in the normative mineral model. Chalcopyrite, chalcocite, and covellite comprise more the 95 percent of the copper-bearing sulphides, with only two samples found to contain more than trace amounts of accessory bornite, idaite, enargite and/or tennantite (Table 4). Variations in the colour and anisotropy of the copper sulphides were commonly observed, thus indicating copper minerals with a composition intermediate to chalcocite and covellite. Nonetheless, these minerals were tabulated as either chalcocite or covellite according to grey v. blue anisotropic character, respectively, rather than as distinct intermediate mineral species. Microprobe and XRD analyses conducted within the study suggested that stoichiometric chalcocite (Cu2S) rarely occurs in these samples. Instead, djurleite (Cu1.95S) is the most common composition of the grey copper sulphides, and was adopted as composition of the ‘chalcocite’ end-member (Williams et al. 2000).

Modal mineral content of the heavy mineral separate adjusted by weight fraction of the separate is reported for the reconstructed sample, as are the copper and sulphur values calculated from the modal minerals. Consistent with the findings from mass balance calculations in one of the verification samples, copper and sulphur content estimated from the modal mineralogy are lower than assayed values for the coarse fractions, reflecting the low levels of separation. Differences between estimated and assayed values decrease with finer size fractions, to the extent that estimated values are generally higher than assays in the −100 mesh fraction. This is due to the high proportion of sulphides reporting to the heavy separate, combined with an estimation method that ignores the non-sulphide fraction of the heavy minerals. This further confirms the findings from the mass balance calculations, and provides a high level of confidence on the mineral ratios obtained in modal analysis of these finer size fractions.

The FSCu/TCu ratios are plotted against CNCu/TCu ratios in Figure 1, comparing the partial extraction ratios of the verification samples with those of the calibration standards. The extent of the data distribution is indicated by a triangle that connects the extraction ratios of the three major minerals: chalcocite, covellite and chalcopyrite. The verification samples fall completely within this compositional triangle, except for slight analytical variations at the chalcocite and chalcopyrite vertices. Pairs of verification points scattered through compositional space reflect the large differences in mineralogy between samples and the small differences among size fractions in each sample.

Results of the Na2CO3 sulphate sulphur tests are presented in Table 5, where the average and standard deviation of the tests performed in duplicate are presented. Pyrite is stable in the digestion, as it solubilizes less than 1% of total sulphur in the pyrite sample. Tests on mineral separates and mineral mixtures indicate that Na2CO3 is not a highly effective wash at these relatively high sulphate sulphur concentrations, providing incomplete digestion for both sulphate minerals. The method solubilized c. 30% of the available sulphur in the jarosite sample and 65% in the gypsum sample (Table 5). However, the method becomes more effective at lower concentrations extracting 47% of sulphate sulphur available in the pyrite-jarosite mixture and 89% in the pyrite-jarosite-gypsum sample (Table 5).

These results were qualitatively confirmed in a second phase of tests, in which two synthetic samples were construction from mixtures of the mineral separates. The 5% NaOH digestion was selected as the alternative to compare with the Na2CO3 standard digestion, both of are shown compared in Table 5 to the calculated head grades of the two synthetic samples. Correcting for the differences in the calculated and actual head grade, the amount of soluble sulphur obtained in 5% NaOH is 100% of sulphates in the pyrite-jarosite sample and 97% of the pyrite-jarosite-calcium sulphate sample. Soluble sulphur in the Na2CO3 digestion was 47% of sulphate sulphur in the pyrite-jarosite sample (compared to 31% expected from the mineral separate) and 89% of sulphates in the complex mixture (compared to 55% soluble expected from the mineral separates).

Normative mineral estimation

It has been empirically established in this study and widely reported in the metallurgical and analytical chemistry literature that copper content extracted from a specific mineral by a given chemical digestion is generally dependent upon the concentration of the mineral (i.e. dissolution occurs at a constant extraction ratio). In addition, dissolution of multiple minerals in finely pulverized samples can be assumed to behave as a physical mixture, an assumption supported by calibration studies. Thus TCu, FSCu and CNCu analyses of a particular sample can be treated mathematically as the sum of the mineral concentrations, weighted by the respective extraction rates. This simple observation provides the basis for normative mineral estimates from the partial extraction analyses.

Quantitative interpretation of the partial extraction analyses depends on an a priori knowledge of the copper mineral assemblage and the behaviour of those minerals in the analyses. Geological observations made during evaluation of the Escondida Norte deposit established that the supergene and hypogene sulphide mineralization can be effectively treated as a system consisting of chalcocite, covellite, chalcopyrite, and pyrite. However, minor amounts of bornite, enargite, tennantite and other copper-bearing sulphides are known to be present from observations under hand lens and petrographic microscope, and could be important minerals for other deposits.

Normative Mineral Equations

A system of simultaneous equations can be written for a given sample by using the mineral extraction rates as known constants, the partial extraction results of that sample as known variables, and the corresponding mineral content as unknown variables. In order to obtain exact solutions, the system requires an equal number of equations and unknown variables. Thus for the system chalcopyrite-covellite-chalcocite that is assumed for the Escondida Norte sulphide mineralization, three equations can be defined for each sample using the three copper analyses:(1)(2)(3)where TCu, CNCu, and FSCu correspond to the results of the referenced chemical analysis in weight percent copper, and the symbol X refers to the fraction of copper that the superscripted mineral is extracted in the subscripted analysis. The unknown variables cp, cv, and cc were given the term Copper Source Ratio (CSR) and represent the fraction of total copper contained in chalcopyrite, covellite, and chalcocite, respectively. Assuming that the copper sulphides are completely soluble in the total copper analysis and are the only copper-bearing minerals in the sample, Equation 1 simplifies to:(4)This assumption simplifies the system of the above equations such that the relative mineral abundances may be explicitly solved by the following set of equations:(5)The Copper Source Percent (CSP), or weight percent copper contained in each mineral is determined by multiplying the respective CSR by the total copper content of the sample. Normative mineral content (in weight percent) is calculated from the CSP and copper content of the respective minerals. The iron and sulphur contents of the normative copper sulphides are then deducted from the respective chemical analysis in order to estimate the normative pyrite content.

Normative pyrite is calculated from residual iron and residual sulphur and compared to each other to select the best estimate. If the absolute difference between the two pyrite estimates is within the analytical precision of their average value, the average is accepted. If the difference is outside the analytical precision, then the smaller of the two is accepted. Only rarely was pyrite estimated from residual iron selected as the best value. The sulphur-based estimate was usually selected in samples lower than c. 6 wt. % pyrite, while the average value was more common in samples with higher pyrite content.

Mineral extraction rate constants

A key assumption in the estimation of normative mineral abundances is that the fraction of copper extracted from the end-member minerals are known constants. Copper extraction values of the sulphide and sulphosalt minerals tested in this study are similar to those reported in the literature (Table 1). However, the bulk of extraction values provided in the literature were based on metallurgical-style tests over a wide range of time, temperature, and particle size. The analytical results obtained in this study (Tables 3 and 4) were performed under a set of standard conditions and with a high degree of reproducibility for a given sample. Partial copper extraction values for each the three end-member minerals defined for the Escondida Norte mineral resource were obtained from calibration and verification samples of appropriate mineralogy. Consistent with the formulation of the normative mineral estimates in Equation 5, constants for each partial extraction will be determined as a ratio to total copper.

Chalcopyrite comprises nearly all observed copper minerals in the calibration standards MI-01 and LK-New2 (Table 2), as well as verification sample ZERD-128 326-340 (Table 3). Chalcocite was used to construct mineral standard MORKV (Table 2) while calibration and verification samples were confirmed by microprobe or XRD to contain djurleite: ZERD-135 220-234, and ZERD-166 234-250. Copper sulphides in verification sample ZERD-66 200-216 were also found by Chávez (1999) to be essentially pure ‘chalcocite’ (Table 3), presumably of djurleite composition.

The CNCu and FSCu analyses of these calibration and verification samples are plotted against TCu in Figure 2a and b, respectively. The calibration samples are labelled in each scatter plot for clarity. The data form two linear trends, one created by chalcocite-bearing samples, the other by chalcopyrite-bearing sample. Both show a high degree of correlation with intercepts near the axis origin. These are conditions under which the mineral extraction ratios are best determined by linear regression techniques (e.g. Koch & Link 1980). An initial regression was performed to determine the origin in each of the four linear regression equations, finding that the standard linear equations have origins that are statistically identical to zero (95% confidence). Accordingly, linear regression was performed by fixing the origin coefficient to zero, so that the slope of the regression line is equivalent to the average partial extraction ratio of the target mineral. The regression lines are presented against the raw data in Figure 2, and regression statistics are presented in Table 6. Adopting the regression line statistics as the end-member extraction values, ratios of 0.096 ± 0.018 CNCu/TCu and 0.049 ± 0.012 FSCu/TCu are assumed for chalcopyrite, while 0.98 ± 0.022 CNCu/TCu and 0.506 ± 0.008 FSCu/TCu are applied to ‘chalcocite’.

Nearly pure covellite is only found in calibration sample AR-47/105, which gave partial extraction ratios of 0.961 ± 0.021 CNCu/TCu and 0.035 ± 0.002 FSCu/TCu (Table 3). These values are consistent with extraction ratios extracted from published and unpublished reports (Table 1), and with covellite-rich verification samples ZERD-48 272-288 and ZERD-220R 144-210 (Table 3). Other copper mineral phases that are occasionally observed in drill core include enargite, tennantite, and bornite. None of these minerals were found in sufficiently pure amounts for independent confirmation of the mineral standards results using 2-meter or 15-meter drill hole intervals. The extraction ratios determined from the respective standard samples are therefore assumed for these mineral species, where necessary.

The extraction constants derived for the end-member minerals ‘chalcocite’, covellite, and chalcopyrite form the vertices of the compositional triangle plotted in Figure 1. Djurleite was assumed as the composition for ‘chalcocite’, while stoichiometric compositions were assumed for the covellite and chalcopyrite components.

Verification of normative mineral estimates

The normative mineralogy of the verification samples were estimated according to Equation 5 with a commercial spreadsheet program that links the end-member standard extraction rates to the partial extraction data. Copper normative mineral content of each sample is calculated in three spreadsheet cells, each coded with one of the three solutions to mineral CSR. (Eq. 5) The spreadsheet application included adjustments to correct those CSR values that calculate to be greater than one or less than zero. Adjustments consisted of setting negative ratios to zero, while maintaining a sum of 1.0 at constant proportions of those minerals with positive CSR's. These samples can be recognized in Figure 1 as those that plot outside the triangle formed by the three mineral components, falling near the mineral end-members or near a compositional tie line between two minerals. The magnitude of the compositional errors seen in these samples is consistent with analytical uncertainty, on the order of ±0.05 CSR.

Normative mineral estimates and analytical precision of the Escondida Norte verification samples are presented in Table 7 in comparison with the adjusted modal mineral content and uncertainty. Differences between individual mineral in the modal and normative estimates are tabulated as a percentage of the total copper sulphide content. Total difference in Table 7 is calculated from the sum of squared differences in chalcopyrite and covellite, relative to the total copper sulphide content. Normative and modal estimates are graphically compared in Figure 3, where individual minerals are compared in Figure 3a through c, and combined mineral contents are compared in Figure 3d. Error bars in Figure 3a through c reflect the analytical precision at 95% confidence.

Comparison of normative and adjusted modal estimates of copper sulphides, Escondida Norte verification samples (Table 7). (a) Chalcopyrite estimates. (b) Djurleite (‘chalcocite’) estimates. (c) Covellite estimates. Error bars show estimation uncertainty at a 95% confidence level. The least square linear fit to the estimation pairs is shown as solid line, while the 1:1 relationship shown by the dashed line. Linear fit equation and correlation coefficient for each mineral are presented in the respective upper left corner. (d) Combined mineralogy plotting the ratios of chalcopyrite to total copper minerals against covellite to total copper minerals. Dashed lines provide contours of chalcocite to total copper mineral ratio. Tie lines connect modal and normative estimates of the same sample.

Estimates of the three minerals independently compare favourably for the 33 samples as indicated by linear regression statistics. All three regression lines have intercepts near zero, slopes near one, and correlation coefficients greater than 0.94 (Fig. 3). The difference between modal and normative estimates of minerals are generally equal to or less than the corresponding estimation uncertainty. Differences that are larger than the combined estimation uncertainty (95% confidence level) are indicated in Table 7 by underlining, and occur in 16 of the 33 samples Of the 99 individual mineral pairs in the data set, differences of statistical significance occur in 7 pairs of chalcopyrite estimates, 14 djurleite, and 8 covellite pairs.

A test for systematic bias between the methods was based on global averages of minerals within the 33 samples. Modal estimates average 0.10 wt. % greater in chalcopyrite than the normative estimates, and less than 0.01 wt. % greater in combined bornite and enargite. These are offset by estimates of djurleite and covellite that are 0.03 and 0.04 wt. % lower in the normative estimates, respectively. Paired sample t-test on the sample set indicate that the normative djurleite and covellite contents are unbiased compared to the adjusted modal content at a 95% confidence level. The difference in average chalcopyrite content is significant at the same confidence level (Table 8), although it is noted that two samples contribute 60% of the variance.

Statistical comparison of normative and adjusted modal average values of the Escondida Norte verification samples and results of paired two sample t-test (unequal variances) on the hypothesis of that modal and normative means are equal at a significance of 0.05

The previous discussion was based on a model of uncertainty that assumes random and independent errors in the chemical or mineralogical measurement. However, this assumption is violated when comparing the modal and normative estimates. Because each pair of mineral estimates was normalized to the same copper concentration, a degree of freedom was removed from the variation between the two. That is, a positive difference in one mineral must be offset by negative differences in one or both of the other minerals to maintain constant sum of minerals. Just like ternary mineral content in a closed system can be completely defined with two minerals, variance between normative and modal estimates can be defined for a given sample as the sum of squared differences of two minerals.

The relative differences between the modal and normative estimates of the complete sample mineralogy are presented in Figure 3d, where the ratio of covellite to total copper sulphides are plotted against the ratio of chalcopyrite to total copper sulphides. The djurleite mineral fraction is defined by the sum of chalcopyrite and covellite mineral fractions as contoured in Figure 3d by the grey dashed lines. Chalcopyrite and covellite were chosen as the two components for determining differences between the normative and modal estimates as the relative errors of these minerals presented in Table 7 are uncorrelated with each other (R2 = 0.053), and both are negatively correlated with djurleite. The square root of the squared difference is equivalent to the length in the tie lines in Figure 3d that connect normative and modal estimates, and is converted to percentage of the total copper value for reporting total percent difference in Table 7.

Total differences between modal and normative estimates are less than 10% of the total copper sulphide content in twenty-four of the thirty-three verification samples, while differences greater than 20% are observed in three samples. The larger combined differences tend to be associated with larger differences in chalcopyrite and in samples with intermediate compositions. This relationship is illustrated in Figure 4, where squared differences between normative and modal mineral estimates are plotted against the chalcopyrite mineral fraction of the modal estimates. Samples that are near the upper and lower limits of chalcopyrite fraction exhibit uniformly low differences between estimates, with variances increasing with intermediate compositions. A least squares fit that uses a second order polynomial equation indicates that the errors approximate an X(1-X) distribution, which is also the form of the variance of the binomial distribution that is commonly used for estimating errors with point count estimation techniques (e.g. van der Plas & Tobi 1965). Samples with differences that exceed this relationship are characterized by modal chalcopyrite estimates significantly higher than normative, exceeding the variances expected from estimation uncertainty. The most likely source of these variances are in the modal estimates, as the FSCu and CNCu values calculated from modal mineralogy in these samples do not correspond to the analytical values. The most likely cause of the error is a counting bias toward chalcopyrite when encountering grains of chalcopyrite partially replaced by supergene sulphides.

Relationship of sulphide mineral content and the total squared difference between normative and adjusted modal estimates of copper sulphides, Escondida Norte verification samples. Symbols plot the distribution of the ratio of chalcopyrite to total copper sulphides (adjusted modal estimate, Table 7) to the squared difference between modal and normative estimates (square of the relative differences shown in Table 7 and Fig. 3d). The dashed line is the least squares polynomial regression fit to the squared differences with the regression equation.

Discussion

The partial extraction and normative mineral tool kit described here was developed and implemented as part of the Escondida Norte project. As the techniques proved to be a valuable tool to aid in the geological and economic evaluation of the deposit, it was subsequently integrated as a routine activity in the geological logging and assaying protocols of Minera Escondida operations. Within this context, the method has been continuously and consistently monitored to maintain analytical quality and validity of the interpreted mineralogy. Good quality chemical analyses that are distributed over the complete drilling program are important for a high degree of confidence on the downstream geological, mine planning, and metallurgical applications. Incorporation of quality control protocols that track analytical bias and precision over time are also important components of the program, as are independent checks of the normative mineral assumptions and interpretations.

While the methods and analytical approach presented here are portable to other mineral deposits, the specific details on chemical digestion and normative mineral components will likely need modification. Successful implementation of the partial extraction analytical protocols and determination of normative mineral content depend on paying attention to a couple of key concepts: consistent attention to analytical quality and interpretative results and a priori knowledge of the copper mineralogy. Interpretation and communication of the normative mineral estimates led to some important insights and cautions as they were applied to different deposits and support for metallurgical characterization and forecasting.

Application in bornite-bearing systems

Escondida Norte is a porphyry copper deposit with simple primary sulphide mineral assemblage of pyrite and chalcopyrite overprinted by supergene enrichment. The ternary copper system of chalcopyrite-chalcocite-covellite was well described by the TCu, CNCu, and FSCu analyses as previously discussed. In the years since partial extraction was developed for Escondida Norte, the tool has been implemented in other mineral deposits and projects and adapted to account for the differing copper mineralogy. Bornite and enargite are common phases in hypogene zones, while complete to partial oxidation of sulphides will result in phases such as chrysocolla, brochantite, or malachite. In addition, the tools have been adapted to characterize heap leach test samples and industrial scale stockpiles, both for pre-leach mineralogy and the post-leaching residual phases.

The most straightforward adaptation is the use of ferric sulphate and cyanide-soluble copper in bornite-chalcopyrite-magnetite zones of porphyry copper and skarn deposits. Presented in Figure 5 are the partial extraction analytical ratios of samples from Pampa Escondida porphyry copper, Chile (Hervé et al. 2012); Tintaya copper-gold skarn, Peru; and Antapaccay porphyry copper, Peru (Perelló et al. 2003). Sample mineralogy consists of chalcopyrite ± bornite ± chalcocite/digenite that was determined by visual and microscopic analysis. The average analytical ratios of the end-member minerals (Fig. 1; Table 3) are presented for reference. The analytical ratios of the samples fall along the linear tie line between chalcopyrite and bornite, consistent with the modal mineral observations. The amount of scatter around the tie line is consistent with the magnitude of the analytical precision, but minor amounts (<0.05 wt. % mineral) of chalcocite (digenite?) and covellite were noted in many of the QEMScan analyses. Significant amounts of chalcocite were noted in two of the samples, as indicated by the cross symbol in Figure 5.

In the simplest case, the normative sulphide mineral system could be approximated by the binary chalcopyrite-bornite, thus requiring only one of the two partial extraction analyses plus total copper to arrive at the exact solution to a problem with two unknowns. However, the assemblage of chalcopyrite-bornite-chalcocite (digenite) is commonly associated with high-sulphidation porphyry copper and epithermal mineralization (e.g. Yund & Kullerud 1966), and a ternary normative mineral system will be required to distinguish bornite from chalcocite. In this case, one would only need to modify the end-member components for the normative calculation from the two assay ratios, conducting studies to determine the composition and behaviour in FSCu and CNCu of the selected end-member minerals; that is, chalcopyrite-digenite-bornite in place of chalcopyrite-chalcocite-covellite. As a final note, normative pyrite is consistently near zero in these bornite-chalcopyrite samples, consistent with mineralogical observations.

In a more complex mineralogical systems (e.g. supergene chalcocite-covellite overprinting chalcopyrite-bornite), a third partial extraction analysis will be required to maintain an exact solution of the normative equations. The extraction ratios for chalcocite, bornite, and covellite are nearly collinear in coordinates of FSCu/TCu v. CNCu/TCu, meaning that bornite cannot be uniquely defined from chalcocite + covellite using only these two ratios. The additional partial extraction analysis must be able to uniquely distinguish one of these three minerals from the others in order to confidently quantify the normative association. Preliminary studies into this problem have suggested that organic or non-organic ligands (e.g. citric acid or ammonia) show potential as a third partial digestion, resulting in 15 – 20% extraction of copper in chalcocite and 2 – 5% extraction from the other phases, including bornite.

Application in oxide copper systems

While a four-component system has not been required for the bornite-bearing systems that have thus far been evaluated, a system of similar complexity has been successfully implemented to characterize oxidized mineralization in the leached cap of porphyry copper deposits. The mineral character of higher-grade copper in a leached cap has historically been made on the basis of acid-soluble copper (SCu) and total copper, thus making an implicit assumption of a binary oxide-sulphide mineralogical system. However, where included in the analytical protocol, FSCu and CNCu behaviour indicate the existence of more complicated mineralogy in both the acid-soluble and insoluble fractions. Better visibility on these additional components could significantly improve both the geological interpretation and metallurgical characterization.

Weathered zones that overlie supergene enriched sulphides generally contain low copper content (<0.10 wt. % Cu), but are of extreme geological interest because of the mineralogy and texture of residual iron and sulphur phases that provide evidence of the pre-existing sulphide mineralization and guide exploration of the underlying supergene deposit (e.g. Anderson 1982; Alpers & Brimhall 1989). Of potential interest for mineral resource development studies, however, is the common occurrence of high grade copper mineralization in the oxidized cap, where copper leaching was ineffective or incomplete.

Oxide copper mineralization has been interpreted as result of the supergene leaching process rendered ineffective due to reactive host rocks or low pyrite to copper sulphide ratios (Anderson 1982; Cook 1988; Chávez 2000). Where the precursor copper sulphides were dominated by chalcocite-bearing sulphides, the initial mineral phases are generally hydroxyl-bearing cupric salts bound to water-soluble anions such as , Cl−, or (e.g. brochantite, antlerite, atacamite, azurite, and malachite). Chrysocolla-bearing mineralization, on the other hand, is interpreted as forming in moderate to high pH environments, such as oxidation of precursor chalcopyrite mineralization with low pyrite content, in transported (exotic) deposits, or late in the oxidation profile and replacing early cupric hydroxysalt minerals (Anderson 1982; Cook 1988; Munchmeyer 1996; Chávez 2000).

Samples were collected from Escondida Norte (Chile) and the Globe-Miami district (Arizona) for calibration of partial extraction methods and selected for mineral purity on the basis of hand lens examination supported by petrographic microscopy. The samples were submitted for analysis using the partial extraction protocol previously described, but also including an SCu analysis. This analytical protocol thus provides three ratios for each sample and a set of four normative mineral equations, allowing for the exact solution of four mineral components.

The analytical behaviour of the samples presented in Figure 6 exhibit relatively tight clustering in the three dimensions of CNCu/TCu, SCu/TCu, and FSCu/TCu, based on copper mineralogy. A perspective view of the three-dimensional graph is provided in Figure 6a, with a projection of the data to the three binary graphs presented in Figure 6b through d. The extraction ratios of end-member components of the potential normative mineral associations are presented for chalcocite and chalcopyrite in previous discussions, but also include those for the hydroxyl-bearing cupric salts (CUOX), chrysocolla (XC), and a poorly defined copper-bearing goethite phase (CUFE).

Malachite and antlerite-brochantite were included in the sample set of Figure 6, and similar results have also been obtained from atacamite and azurite. These CUOX minerals are essentially 100% soluble in all of the partial extraction analyses, although average values of samples sets are slightly lower due to small amounts of less soluble copper phases and a reluctance of analytical labs to report analytical results where TCu is less than the partial extraction analyses. Where the oxidation process was incomplete, the oxide minerals are typically physically intermixed with chalcocite-bearing sulphides, with mixed oxide-sulphide phases trending along the CUOX-CC tie line.

Chrysocolla, a hydrous copper silicate with low crystallinity, is characterized by high solubility in acid digestion (FSCu/TCu and SCu/TCu >0.8), but low solubility in sodium cyanide (CNCu/TCu between 0.1 to 0.25, Fig. 6). As observed in Figure 6b and d, the CNCu/TCu ratios of chrysocolla samples increase with decreasing acid solubility, while both oxidizing and reduced acid digestions are positively correlated (Fig. 6c). These variations occur both within a single deposit and between mineral deposits. However, chrysocolla is commonly associated with copper hydroxysalts and a number of poorly defined phases, such as copper clays, copper pitch, and copper wad (Cook 1988; Chávez 2000; Mote et al. 2001) that will also create variability in the end-member assumptions.

In all of the deposits that have thus far been tested by partial extraction, chrysocolla mineralization is also associated with an iron oxy-hydroxide phase containing 1 – 5 wt. % Cu that is insoluble in the three partial extraction analyses (labelled CUFE in Fig. 6). Detailed SEM examination of selected samples found increased copper content in ferric mineral grains that is associated with elevated aluminium and silicate content. The phase is in sufficient quantities to account for a large fraction of the refractory copper in chrysocolla-bearing oxide capping, although other refractory phases such as remnant chalcopyrite and native copper may also be observed as fine intergrowths with iron oxides (Baum 1998; Thomas 2007).

The partial extraction ratios of a few leached capping samples are plotted in Figure 6 for comparison with the oxide copper samples. Leached capping is characterized by the presence of ferric (hydroxy-)oxide boxworks after precursor sulphides, locally with small amounts of copper pitch or wad, and generally contains less than c. 0.1 wt. % TCu. Ratios of soluble copper to total copper are less than 0.5 and nearly equal in all three extractions. Because the low copper content, copper deportment of the leached capping has not been included in these studies nor applied to mineral resource characterization.

Normative equations based on four copper analyses allow the designation of four mineral components. The geological associations briefly summarized above suggest that two distinct 4-component normative systems can be defined to reduce the overall complexity of the mineralogy while closely approximating the metallurgical behaviour of the actual mineralization. In most cases, the normative components of CC-CUOX-XC-CUFE is a good approximation of oxide minerals zone, including partially oxidized sulphides. Cases have been encountered where weakly oxidized supergene sulphides will consist of chalcocite-covellite overprinted by copper sulphates. The mineralogy of these zones can be estimated with the end-member normative components of antlerite-chalcocite-covellite-chalcopyrite. This set of components extends the normative triangle developed for the sulphide enrichment zone and is consistent with partial extraction ratios of this zone.

While the normative mineral components suggested here will necessarily simplify the true mineralogy, this approach does provide a significant improvement over a protocol that only uses the SCu/TCu ratio. While the metallurgical behaviour of chrysocolla and the copper hydroxysalts are similar to each other in heap leach processing, understanding the geological distribution of different geochemical environments is important for resource definition studies. The ability to distinguish remnant chalcocite from the refractory Cu-Fe phase in low SCu/TCu mineralization does directly improve metallurgical characterization as they will have different behaviour in heap leach plants.

Conclusions

The studies presented in this communication were conducted in order to solve a problem that is common to most mineral resource development studies: provide sufficient understanding of the deposit ore mineralogy to confidently select the correct processing option and optimize project value. Methods that were in common use at the time of this study primarily consisted of visual estimates made during logging and petrographic estimates on specimens or composite samples. Visual logging of drill core and chip samples typically supports understanding of spatial distribution of mineral abundances, while hand sample and thin section petrographic studies provide understanding of the paragenesis and textural associations. Partial extraction and normative mineralogy does not replace geological logging and petrographic analysis, but instead bridges the gap between them. The tools developed for the Escondida Norte project provide quantitative mineral estimates at a reasonable cost that combines the ubiquity of geological logging at a level of accuracy similar to the limited number of samples for petrographic and spectral mineral analysis.

The partial extraction program should be integrated as a routine activity in the geological logging and assaying system, and be continuously and consistently monitored to maintain analytical quality and validity of the interpreted mineralogy. Good quality chemical analyses that are distributed over the complete drilling program are important for a high degree of confidence on the downstream geological, mine planning, and metallurgical applications. Incorporation of quality control protocols that track analytical bias and precision over time are also important components of the program, as are independent checks of the normative mineral interpretation.

Normative estimates of copper-iron sulphide mineral content were utilized by the Escondida Norte project and subsequently by Escondida operations in several important ways. The normative mineral estimates were compared with visual estimates in drill hole logs, providing feedback to the team of geologists and informing the assigned mineral zone code used for geological modelling and grade estimation. The density of high quality normative mineralogy was sufficient to permit estimation of the mineral content in the mineral resource model. Mineralogy in the block model was primarily used to support metallurgical models for sulphide heap bioleach recovery and concentrate copper grade, used in economic and marketing forecasting.

Normative mineralogy itself is more logically related to potential metallurgical behaviour of the material under study, particularly for the heap leaching process, as it is a measure of the chemical response of the mineral phases rather than their optical or spectral properties. While normative mineralogy should be broadly equivalent to modal analysis, local variations may be expected due to differences in the properties being observed or measured for a given mineral component. To maintain internal consistency, partial extraction analysis was also incorporated into the protocols for characterizing and modelling metallurgical behaviour.

Importantly, the tool kit provides information that is directly attributable to the copper-iron sulphide mineralogy, as opposed to prediction of a metallurgical result. The relatively dense sampling grid of high quality sulphide mineral abundances provides for an improved geological understanding of the distribution of supergene mineral abundances. These combine to improve quality of computerized geological models of mineralization and controls on copper grade and geometallurgical behaviour.

Acknowledgements

The work described in this paper was largely completed while the authors were employed by BHP Billiton or Minera Escondida, Ltda. and assigned to the Escondida Norte project. Kevin O'Kane is gratefully acknowledged for finding space in the project budget to fund the proof of concept of these methods. The study was made possible by the mineralogical and geological observations of the Escondida Norte project team. Our special thanks go to Bill Lehmbeck and Jim Martin (Skyline Assayers and Laboratories) for their insights into analytical chemistry. We would like to thank BHP and Minera Escondida Ltda. for permission to publish the data. A previous version of this manuscript greatly benefited from reviews and comments by William X. Chávez and Mary Doherty.